In this paper, the performance of the Singular Spectrum Analysis (SSA) technique is assessed by applying it to 24 series measuring the monthly seasonally unadjusted industrial production for important sectors of the German, French and UK economies. The results are compared with those obtained using the Holt-Winters' and ARIMA models. All three methods perform similarly in short-term forecasting and in predicting the direction of change (DC). However, at longer horizons, SSA significantly outperforms the ARIMA and Holt-Winters' methods.
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